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Full-Text Articles in Engineering

Enterprise Environment Modeling For Penetration Testing On The Openstack Virtualization Platform, Vincent Karovič Jr., Jakub Bartaloš, Vincent Karovič, Michal Greguš Dec 2021

Enterprise Environment Modeling For Penetration Testing On The Openstack Virtualization Platform, Vincent Karovič Jr., Jakub Bartaloš, Vincent Karovič, Michal Greguš

Journal of Global Business Insights

The article presents the design of a model environment for penetration testing of an organization using virtualization. The need for this model was based on the constantly increasing requirements for the security of information systems, both in legal terms and in accordance with international security standards. The model was created based on a specific team from the unnamed company. The virtual working environment offered the same functions as the physical environment. The virtual working environment was created in OpenStack and tested with a Linux distribution Kali Linux. We demonstrated that the virtual environment is functional and its security testable. Virtualizing ...


Understanding Students’ Global Interdependence In Science Instruction, Walter S. Smith Dec 2021

Understanding Students’ Global Interdependence In Science Instruction, Walter S. Smith

Journal of Global Education and Research

Multiple American educational organizations such as the National Education Association, Association for Supervision and Curriculum Development, and the Council of Chief State School Officers have advocated for globalizing the K-12 curriculum. The National Science Teaching Association (NSTA) in a position statement on international education and the Next Generation Science Standards have produced goals and standards for internationalizing the science curriculum by addressing topics such as climate change, environment, and disease that cross borders. In contrast to those pronouncements on the curriculum, this article views global science education through an instructional lens that focuses on a students’ global interdependence in science ...


Renewing The Paradigm: Simulating The Miso Region Electrical Grid Using Renewable Energy Generation With Implementation Of Long-Term Hydrogen Storage, Jackson C. Henningfield May 2021

Renewing The Paradigm: Simulating The Miso Region Electrical Grid Using Renewable Energy Generation With Implementation Of Long-Term Hydrogen Storage, Jackson C. Henningfield

Macalester Journal of Physics and Astronomy

The current electrical grid regime is not optimized to include renewable sources of power generation such as wind and solar. Electrical storage, as of now, is primarily established through the short-term generation and demand-meeting consumption leaving much of the grid susceptible to inefficiencies and power loss during natural events that leave grids out of commission. Delineating a new type of long-term storage, a hydrogen fuel cell, would ensure a reliable source of power to the masses regardless of the physical and climatic geography. The MISO region provides a perfect case study to introduce the ideas of diverse energy generation and ...


Pharyngeal Constriction As A Cause For Late Acquisition And Speech Sound Disorders Of Rhotic Sounds In English, Spanish, And French, Connor Mahon May 2021

Pharyngeal Constriction As A Cause For Late Acquisition And Speech Sound Disorders Of Rhotic Sounds In English, Spanish, And French, Connor Mahon

The Downtown Review

This paper attempts to explain why rhotic sounds are cross-linguistically late developing among the sound inventory of children. Included is a summary of the current literature regarding classification of rhotic sounds, an examination of the articulatory movement of the tongue root, and an overview of the clinical implications on the field of speech-language pathology. The evidence presented supports the hypothesis that pharyngeal constriction is characteristic of rhotic sounds in many languages, and that it is related to the relative late acquisition and higher rate of speech sound disorders, as seen in English, Spanish, and French.


Collaborative City Digital Twin For The Covid-19 Pandemic: A Federated Learning Solution, Junjie Pang, Yan Huang, Zhenzhen Xie, Jianbo Li, Zhipeng Cai May 2021

Collaborative City Digital Twin For The Covid-19 Pandemic: A Federated Learning Solution, Junjie Pang, Yan Huang, Zhenzhen Xie, Jianbo Li, Zhipeng Cai

Tsinghua Science and Technology

The novel coronavirus, COVID-19, has caused a crisis that affects all segments of the population. As the knowledge and understanding of COVID-19 evolve, an appropriate response plan for this pandemic is considered one of the most effective methods for controlling the spread of the virus. Recent studies indicate that a city Digital Twin (DT) is beneficial for tackling this health crisis, because it can construct a virtual replica to simulate factors, such as climate conditions, response policies, and people’s trajectories, to help plan efficient and inclusive decisions. However, a city DTsystem relies on long-term and high-quality data collection to ...


A Data-Driven Clustering Recommendation Method For Single-Cell Rna-Sequencing Data, Yu Tian, Ruiqing Zheng, Zhenlan Liang, Suning Li, Fang-Xiang Wu, Min Li May 2021

A Data-Driven Clustering Recommendation Method For Single-Cell Rna-Sequencing Data, Yu Tian, Ruiqing Zheng, Zhenlan Liang, Suning Li, Fang-Xiang Wu, Min Li

Tsinghua Science and Technology

Recently, the emergence of single-cell RNA-sequencing (scRNA-seq) technology makes it possible to solve biological problems at the single-cell resolution. One of the critical steps in cellular heterogeneity analysis is the cell type identification. Diverse scRNA-seq clustering methods have been proposed to partition cells into clusters. Among all the methods, hierarchical clustering and spectral clustering are the most popular approaches in the downstream clustering analysis with different preprocessing strategies such as similarity learning, dropout imputation, and dimensionality reduction. In this study, we carry out a comprehensive analysis by combining different strategies with these two categories of clustering methods on scRNA-seq datasets ...


A Computer-Aided System For Ocular Myasthenia Gravis Diagnosis, Guanjie Liu, Yan Wei, Yunshen Xie, Jianqiang Li, Liyan Qiao, Ji-Jiang Yang May 2021

A Computer-Aided System For Ocular Myasthenia Gravis Diagnosis, Guanjie Liu, Yan Wei, Yunshen Xie, Jianqiang Li, Liyan Qiao, Ji-Jiang Yang

Tsinghua Science and Technology

The current mode of clinical aided diagnosis of Ocular Myasthenia Gravis (OMG) is time-consuming and laborious, and it lacks quantitative standards. An aided diagnostic system for OMG is proposed to solve this problem. The values calculated by the system include three clinical indicators: eyelid distance, sclera distance, and palpebra superior fatigability test time. For the first two indicators, the semantic segmentation method was used to extract the pathological features of the patient’s eye image and a semantic segmentation model was constructed. The patient eye image was divided into three regions: iris, sclera, and background. The indicators were calculated based ...


Robust Segmentation Method For Noisy Images Based On An Unsupervised Denosing Filter, Ling Zhang, Jianchao Liu, Fangxing Shang, Gang Li, Juming Zhao, Yueqin Zhang May 2021

Robust Segmentation Method For Noisy Images Based On An Unsupervised Denosing Filter, Ling Zhang, Jianchao Liu, Fangxing Shang, Gang Li, Juming Zhao, Yueqin Zhang

Tsinghua Science and Technology

Level-set-based image segmentation has been widely used in unsupervised segmentation tasks. Researchers have recently alleviated the influence of image noise on segmentation results by introducing global or local statistics into existing models. Most existing methods are based on the assumption that the distribution of image noise is known or observable. However, real-time images do not meet this assumption. To bridge this gap, we propose a novel level-set-based segmentation method with an unsupervised denoising mechanism. First, a denoising filter is acquired under the unsupervised learning paradigm. Second, the denoising filter is integrated into the level-set framework to separate noise from the ...


Efficient Scheduling Mapping Algorithm For Row Parallel Coarse-Grained Reconfigurable Architecture, Naijin Chen, Zhen Wang, Ruixiang He, Jianhui Jiang, Fei Cheng, Chenghao Han May 2021

Efficient Scheduling Mapping Algorithm For Row Parallel Coarse-Grained Reconfigurable Architecture, Naijin Chen, Zhen Wang, Ruixiang He, Jianhui Jiang, Fei Cheng, Chenghao Han

Tsinghua Science and Technology

Row Parallel Coarse-Grained Reconfigurable Architecture (RPCGRA) has the advantages of maximum parallelism and programmable flexibility. Designing an efficient algorithm to map the diverse applications onto RPCGRA is difficult due to a number of RPCGRA hardware constraints. To solve this problem, the nodes of the data flow graph must be partitioned and scheduled onto the RPCGRA. In this paper, we present a Depth-First Greedy Mapping (DFGM) algorithm that simultaneously considers the communication costs and the use times of the Reconfigurable Cell Array (RCA). Compared with level breadth mapping, the performance of DFGM is better. The percentage of maximum improvement in the ...


Game Theoretical Approach For Non-Overlapping Community Detection, Baohua Sun, Richard Al-Bayaty, Qiuyuan Huang, Dapeng Wu May 2021

Game Theoretical Approach For Non-Overlapping Community Detection, Baohua Sun, Richard Al-Bayaty, Qiuyuan Huang, Dapeng Wu

Tsinghua Science and Technology

Graph clustering, i.e., partitioning nodes or data points into non-overlapping clusters, can be beneficial in a large varieties of computer vision and machine learning applications. However, main graph clustering schemes, such as spectral clustering, cannot be applied to a large network due to prohibitive computational complexity required. While there exist methods applicable to large networks, these methods do not offer convincing comparisons against known ground truth. For the first time, this work conducts clustering algorithm performance evaluations on large networks (consisting of one million nodes) with ground truth information. Ideas and concepts from game theory are applied towards graph ...


Inertial Motion Tracking On Mobile And Wearable Devices: Recent Advancements And Challenges, Zhipeng Song, Zhichao Cao, Zhenjiang Li, Jiliang Wang, Yunhao Liu May 2021

Inertial Motion Tracking On Mobile And Wearable Devices: Recent Advancements And Challenges, Zhipeng Song, Zhichao Cao, Zhenjiang Li, Jiliang Wang, Yunhao Liu

Tsinghua Science and Technology

Motion tracking via Inertial Measurement Units (IMUs) on mobile and wearable devices has attracted significant interest in recent years. High-accuracy IMU-tracking can be applied in various applications, such as indoor navigation, gesture recognition, text input, etc. Many efforts have been devoted to improving IMU-based motion tracking in the last two decades, from early calibration techniques on ships or airplanes, to recent arm motion models used on wearable smart devices. In this paper, we present a comprehensive survey on IMU-tracking techniques on mobile and wearable devices. We also reveal the key challenges in IMU-based motion tracking on mobile and wearable devices ...


Deep Reinforcement Learning Based Mobile Robot Navigation: A Review, Kai Zhu, Tao Zhang May 2021

Deep Reinforcement Learning Based Mobile Robot Navigation: A Review, Kai Zhu, Tao Zhang

Tsinghua Science and Technology

Navigation is a fundamental problem of mobile robots, for which Deep Reinforcement Learning (DRL) has received significant attention because of its strong representation and experience learning abilities. There is a growing trend of applying DRL to mobile robot navigation. In this paper, we review DRL methods and DRL-based navigation frameworks. Then we systematically compare and analyze the relationship and differences between four typical application scenarios: local obstacle avoidance, indoor navigation, multi-robot navigation, and social navigation. Next, we describe the development of DRL-based navigation. Last, we discuss the challenges and some possible solutions regarding DRL-based navigation.


Decomposition-Based Multi-Objective Optimization For Energy-Aware Distributed Hybrid Flow Shop Scheduling With Multiprocessor Tasks, Enda Jiang, Ling Wang, Jingjing Wang May 2021

Decomposition-Based Multi-Objective Optimization For Energy-Aware Distributed Hybrid Flow Shop Scheduling With Multiprocessor Tasks, Enda Jiang, Ling Wang, Jingjing Wang

Tsinghua Science and Technology

This paper addresses the Energy-Aware Distributed Hybrid Flow Shop Scheduling Problem with Multiprocessor Tasks (EADHFSPMT) by considering two objectives simultaneously, i.e., makespan and total energy consumption. It consists of three sub-problems, i.e., job assignment between factories, job sequence in each factory, and machine allocation for each job. We present a mixed inter linear programming model and propose a Novel Multi-Objective Evolutionary Algorithm based on Decomposition (NMOEA/D). We specially design a decoding scheme according to the characteristics of the EADHFSPMT. To initialize a population with certain diversity, four different rules are utilized. Moreover, a cooperative search is designed ...


Towards "General Purpose" Brain-Inspired Computing System, Youhui Zhang, Peng Qu, Weimin Zheng May 2021

Towards "General Purpose" Brain-Inspired Computing System, Youhui Zhang, Peng Qu, Weimin Zheng

Tsinghua Science and Technology

Brain-inspired computing refers to computational models, methods, and systems, that are mainly inspired by the processing mode or structure of brain. A recent study proposed the concept of "neuromorphic completeness" and the corresponding system hierarchy, which is helpful to determine the capability boundary of brain-inspired computing system and to judge whether hardware and software of brain-inspired computing are compatible with each other. As a position paper, this article analyzes the existing brain-inspired chips’ design characteristics and the current so-called "general purpose" application development frameworks for brain-inspired computing, as well as introduces the background and the potential of this proposal. Further ...


Distributed Scheduling Problems In Intelligent Manufacturing Systems, Yaping Fu, Yushuang Hou, Zifan Wang, Xinwei Wu, Kaizhou Gao, Ling Wang May 2021

Distributed Scheduling Problems In Intelligent Manufacturing Systems, Yaping Fu, Yushuang Hou, Zifan Wang, Xinwei Wu, Kaizhou Gao, Ling Wang

Tsinghua Science and Technology

Currently, manufacturing enterprises face increasingly fierce market competition due to the various demands of customers and the rapid development of economic globalization. Hence, they have to extend their production mode into distributed environments and establish multiple factories in various geographical locations. Nowadays, distributed manufacturing systems have been widely adopted in industrial production processes. In recent years, many studies have been done on the modeling and optimization of distributed scheduling problems. This work provides a literature review on distributed scheduling problems in intelligent manufacturing systems. By summarizing and evaluating existing studies on distributed scheduling problems, we analyze the achievements and current ...


Multi-Agent Modeling And Simulation In The Ai Age, Wenhui Fan, Peiyu Chen, Daiming Shi, Xudong Guo, Li Kou May 2021

Multi-Agent Modeling And Simulation In The Ai Age, Wenhui Fan, Peiyu Chen, Daiming Shi, Xudong Guo, Li Kou

Tsinghua Science and Technology

With the rapid development of artificial intelligence (AI) technology and its successful application in various fields, modeling and simulation technology, especially multi-agent modeling and simulation (MAMS), of complex systems has rapidly advanced. In this study, we first describe the concept, technical advantages, research steps, and research status of MAMS. Then we review the development status of the hybrid modeling and simulation combining multi-agent and system dynamics, the modeling and simulation of multi-agent reinforcement learning, and the modeling and simulation of large-scale multi-agent. Lastly, we introduce existing MAMS platforms and their comparative studies. This work summarizes the current research situation of ...


Convergence Of Broadband And Broadcast/Multicast In Maritime Information Networks, Jun Du, Jian Song, Yong Ren, Jintao Wang May 2021

Convergence Of Broadband And Broadcast/Multicast In Maritime Information Networks, Jun Du, Jian Song, Yong Ren, Jintao Wang

Tsinghua Science and Technology

Recently, the fifth-generation (5G) of wireless networks mainly focuses on the terrestrial applications. However, the well-developed emerging technologies in 5G are hardly applied to the maritime communications, resulting from the lack of communication infrastructure deployed on the vast ocean, as well as different characteristics of wireless propagation environment over the sea and maritime user distribution. To satisfy the expected plethora of broadband communications and multimedia applications on the ocean, a brand-new maritime information network with a comprehensive coverage capacity in terms of all-hour, all-weather, and all-sea-area has been expected as a revolutionary paradigm to extend the terrestrial capacity of enhanced ...


Ambipolar Transport Compact Models For Two-Dimensional Materials Based Field-Effect Transistors, Zhaoyi Yan, Guangyang Gou, Jie Ren, Fan Wu, Yang Shen, He Tian, Yi Yang May 2021

Ambipolar Transport Compact Models For Two-Dimensional Materials Based Field-Effect Transistors, Zhaoyi Yan, Guangyang Gou, Jie Ren, Fan Wu, Yang Shen, He Tian, Yi Yang

Tsinghua Science and Technology

Three main ambipolar compact models for Two-Dimensional (2D) materials based Field-Effect Transistors (2D-FETs) are reviewed: (1) Landauer model, (2) 2D Pao-Sah model, and (3) virtual Source Emission-Diffusion (VSED) model. For the Landauer model, the Gauss quadrature method is applied, and it summarizes all kinds of variants, exhibiting its state-of-art. For the 2D Pao-Sah model, the aspects of its theoretical fundamentals are rederived, and the electrostatic potentials of electrons and holes are clarified. A brief development history is compiled for the VSED model. In summary, the Landauer model is naturally appropriate for the ballistic transport of short channels, and the 2D ...


Design And Tool Flow Of A Reconfigurable Asynchronous Neural Network Accelerator, Jilin Zhang, Hui Wu, Weijia Chen, Shaojun Wei, Hong Chen May 2021

Design And Tool Flow Of A Reconfigurable Asynchronous Neural Network Accelerator, Jilin Zhang, Hui Wu, Weijia Chen, Shaojun Wei, Hong Chen

Tsinghua Science and Technology

Convolutional Neural Networks (CNNs) are widely used in computer vision, natural language processing, and so on, which generally require low power and high efficiency in real applications. Thus, energy efficiency has become a critical indicator of CNN accelerators. Considering that asynchronous circuits have the advantages of low power consumption, high speed, and no clock distribution problems, we design and implement an energy-efficient asynchronous CNN accelerator with a 65 nm Complementary Metal Oxide Semiconductor (CMOS) process. Given the absence of a commercial design tool flow for asynchronous circuits, we develop a novel design flow to implement Click-based asynchronous bundled data circuits ...


Silicon Valley 2.0 May 2021

Silicon Valley 2.0

In The Loop

The DePaul Innovation Development Lab is a collaborative ecosystem that joins business and academia in mutually beneficial, experimental enterprise. Students work in the techcentric think tank and consultancy that turns business problems into functional, testable software prototypes.


Rethink Everything 2: Markets, Globalization, Development, Nikhilesh Dholakia, Deniz Atik May 2021

Rethink Everything 2: Markets, Globalization, Development, Nikhilesh Dholakia, Deniz Atik

Markets, Globalization & Development Review

No abstract provided.


Developing The Creativity Abilities Of Future Vocational Teachers, Asom Mamatqulov Apr 2021

Developing The Creativity Abilities Of Future Vocational Teachers, Asom Mamatqulov

Central Asian Problems of Modern Science and Education

In this article the formation of creativity abilities of future teachers of vocational education, the manifestation of professional and pedagogical creativity through the development of their creative abilities, creative competencies, a s well as the importance of becoming an active participant in the educational process have been discussed.


Pandemic Policymaking, Philip D. Waggoner Apr 2021

Pandemic Policymaking, Philip D. Waggoner

Journal of Social Computing

This study leverages a high dimensional manifold learning design to explore the latent structure of the pandemic policymaking space only based on bill-level characteristics of pandemic-focused bills from 1973 to 2020. Results indicate the COVID-19 era of policymaking maps extremely closely onto prior periods of related policymaking. This suggests that there is striking uniformity in Congressional policymaking related to these types of large-scale crises over time, despite currently operating in a unique era of hyperpolarization, division, and ineffective governance.


Deeppredict: A Zone Preference Prediction System For Online Lodging Platforms, Yihan Ma, Hua Sun, Yang Chen, Jiayun Zhang, Yang Xu, Xin Wang Apr 2021

Deeppredict: A Zone Preference Prediction System For Online Lodging Platforms, Yihan Ma, Hua Sun, Yang Chen, Jiayun Zhang, Yang Xu, Xin Wang

Journal of Social Computing

Online lodging platforms have become more and more popular around the world. To make a booking in these platforms, a user usually needs to select a city first, then browses among all the prospective options. To improve the user experience, understanding the zone preferences of a user’s booking behavior will be helpful. In this work, we aim to predict the zone preferences of users when booking accommodations for the next travel. We have two main challenges: (1) The previous works about next information of Points Of Interest (POIs) recommendation are mainly focused on users’ historical records in the same ...


Estimating Multiple Socioeconomic Attributes Via Home Location—A Case Study In China, Shichang Ding, Xin Gao, Yufan Dong, Yiwei Tong, Xiaoming Fu Apr 2021

Estimating Multiple Socioeconomic Attributes Via Home Location—A Case Study In China, Shichang Ding, Xin Gao, Yufan Dong, Yiwei Tong, Xiaoming Fu

Journal of Social Computing

Inferring people’s Socioeconomic Attributes (SEAs), including income, occupation, and education level, is an important problem for both social sciences and many networked applications like targeted advertising and personalized recommendation. Previous works mainly focus on estimating SEAs from peoples’ cyberspace behaviors and relationships, such as the content of tweets or the social networks between online users. Besides cyberspace data, alternative data sources about users’ physical behavior, like their home location, may offer new insights. More specifically, in this paper, we study how to predict a person’s income level, family income level, occupation type, and education level from his/her ...


Learning Universal Network Representation Via Link Prediction By Graph Convolutional Neural Network, Weiwei Gu, Fei Gao, Ruiqi Li, Jiang Zhang Apr 2021

Learning Universal Network Representation Via Link Prediction By Graph Convolutional Neural Network, Weiwei Gu, Fei Gao, Ruiqi Li, Jiang Zhang

Journal of Social Computing

Network representation learning algorithms, which aim at automatically encoding graphs into low-dimensional vector representations with a variety of node similarity definitions, have a wide range of downstream applications. Most existing methods either have low accuracies in downstream tasks or a very limited application field, such as article classification in citation networks. In this paper, we propose a novel network representation method, named Link Prediction based Network Representation (LPNR), which generalizes the latest graph neural network and optimizes a carefully designed objective function that preserves linkage structures. LPNR can not only learn meaningful node representations that achieve competitive accuracy in node ...


Using Twitter Bios To Measure Changes In Self-Identity: Are Americans Defining Themselves More Politically Over Time?, Nick Rogers, Jason J. Jones Apr 2021

Using Twitter Bios To Measure Changes In Self-Identity: Are Americans Defining Themselves More Politically Over Time?, Nick Rogers, Jason J. Jones

Journal of Social Computing

Are Americans weaving their political views more tightly into the fabric of their self-identity over time? If so, then we might expect partisan disagreements to continue becoming more emotional, tribal, and intractable. Much recent scholarship has speculated that this politicization of Americans’ identity is occurring, but there has been little compelling attempt to quantify the phenomenon, largely because the concept of identity is notoriously difficult to measure. We introduce here a methodology, Longitudinal Online Profile Sampling (LOPS), which affords quantifiable insights into the way individuals amend their identity over time. Using this method, we analyze millions of "bios" on the ...


How To Better Identify Venture Capital Network Communities: Exploration Of A Semi-Supervised Community Detection Method, Hong Xiong, Ying Fan Apr 2021

How To Better Identify Venture Capital Network Communities: Exploration Of A Semi-Supervised Community Detection Method, Hong Xiong, Ying Fan

Journal of Social Computing

In the field of Venture Capital (VC), researchers have found that VC companies are more likely to jointly invest with other VC companies. This paper attempts to realize a semi-supervised community detection of the VC network based on the data of VC networking and the list of industry leaders. The main research method is to design the initial label of community detection according to the evolution of components of the VC industry leaders. The results show that the community structure of the VC network has obvious distinguishing characteristics, and the aggregation of these communities is affected by the type of ...


Sorption-Spectrometric Determination Of Nickel By Monoammonium Salt Of Glycirrizic Acid, Ugilay Abdurakhmanova, Khabibjon Kushiev Apr 2021

Sorption-Spectrometric Determination Of Nickel By Monoammonium Salt Of Glycirrizic Acid, Ugilay Abdurakhmanova, Khabibjon Kushiev

CHEMISTRY AND CHEMICAL ENGINEERING

The aim of this work is to develop a sensitive, selective and rapid method for the determination of nickel ions using the monoammonium salt of glycyrrhizic acid as an analytical reagent. There obtained IR spectra of the nickel diglycyrrhizinate complex. A simple and express spectral method for determination of the nickel ion is presented. The optimal conditions for the determination of the nickel ion are found. Under optimal conditions, a gradual graph was drawn up, which is linear in the concentration range for nickel of 20.0–40.0 μg/25 ml, the composition of the complex of nickel with ...


Features Of Chloridizing Roasting Of Almalyk Mining Metallurgical Combinate Wastes, Malokhat Atamuratova, Dildora Khakimboeva, Khasan Sharipov, Zuhra Kadirova, Tulkin Shakarov Apr 2021

Features Of Chloridizing Roasting Of Almalyk Mining Metallurgical Combinate Wastes, Malokhat Atamuratova, Dildora Khakimboeva, Khasan Sharipov, Zuhra Kadirova, Tulkin Shakarov

CHEMISTRY AND CHEMICAL ENGINEERING

With the aim to develop a comprehensive technology for processing Almalyk Mining Metallurgical Combinate (AMMC) wastes, the influence of chloride additives on the copper and zinc chloride volatilization process is considered. The relationship between presence of the calcium, potassium and sodium chlorides chlorinating additive on the copper and zinc chlorides sublimation from the AGMK wastes at roasting temperatures up to 700-1000˚C was established.