Set Of Hardware Research Articles

Establishing Standard Protocols for Bacterial Culture in Biological Research in Canisters (BRIC) Hardware

Abstract The NASA GeneLab Data System (GLDS) was recently developed to facilitate cross-experiment comparisons in order to understand the response of microorganisms to the human spaceflight environment. However, prior spaceflight experiments have been conducted using a wide variety of different hardware, media, culture conditions, and procedures. Such confounding factors could potentially mask true differences in gene expression between spaceflight and ground control samples. In an attempt to mitigate such confounding factors, we describe here the development of a standardized set of hardware, media, and protocols for liquid cultivation of microbes in Biological Research in Canisters (BRIC) spaceflight hardware, using the model bacteria Bacillus subtilis strain 168 and Staphylococcus aureus strain UAMS-1 as examples.

Traffic Data Analysis Using Automatic Traffic Counter-Cum-Classifier

Objective: With the advancement of new technologies, traffic data can be collected for the development of existing and new infrastructure. In this study, traffic data has been collected using traffic counter-cum-classifier. Method: The automatic data collection system based on pressure sensor has been studied. The instrument collects the data by sensing the hits made by the tyres of the moving vehicles. The paper discusses about the hardware and software set up of the instrument. Findings: The instrument is able to collect and analyze the macroscopic as well as microscopic characteristics of traffic. It senses the hits produced on the Pneumatic Tube by the running vehicles and data is recorded. This recorded data is then converted into the useful information by the software and according to the calibration of the software. The data can be collected and stored on a number of sites and analyzed by the software. Instrument is able to provide the various results related to characteristics of the traffic like total vehicle counts, classification, 85% speed, peak hour, time headway etc. The reports related to analysis of data can be generated in the form of graphs and pie chart etc. Improvements: Further field testing of the instrument in Indian condition can be done and accuracy of the instrument can be compared with manual methods and other automatic methods.

Making IoT with UDOO

The advent of massively interconnected objects, devices, and sensors raises equally substantial challenges regarding the resources that will allow makers to manage the complexity of such systems and to exploit the opportunities such technologies open up. Simplicity in management and a smooth, creative integration of everyday life objects empowered by digital technology in our own environment are two key factors for a successful penetration of Internet of Things (IoT). We present UDOO IoT, a combined set of open hardware (UDOO Quad, Blu and Bricks) and open software (UAPPI, an extension of MIT App Inventor) technologies that allow novices from their early steps in the maker’s world to create their own digital objects connected to the cloud, easily defining custom behavior logic for sensors and actuators. UDOO IoT is illustrated through one of the field studies carried out along its design process.

Demonstration of a variable data-rate free-space optical communication architecture using efficient coherent techniques

The next generation free-space optical (FSO) communications infrastructure will need to support a wide range of links from space-based terminals in low Earth orbit, geosynchronous Earth orbit, and deep space to the ground. Efficiently enabling such a diverse mission set requires an optical communications system architecture capable of providing excellent sensitivity (i.e., few photons-per-bit) while allowing reductions in data rate for increased system margin. Specifically, coherent optical transmission systems have excellent sensitivity and can trade data rate for system margin by adjusting the modulation format, the forward error correction (FEC) code rate, or by repeating blocks of channel symbols. These techniques can be implemented on a common set of hardware at a fixed system baud rate. Experimental results show that changing modulation formats between quaternary phase-shifted keying and binary phase-shifted keying enables a 3-dB scaling in data rate and a 3.5-dB scaling in system margin. Experimental results of QPSK transmission show a 5.6-dB scaling of data rate and an 8.9-dB scaling in system margin by varying the FEC code rate from rate-9/10 to rate-1/4. Experimental results also show a 45.6-dB scaling in data rate over a 41.7-dB range of input powers by block-repeating and combining a pseudorandom binary sequence up to 36,017 times.

SU‐F‐T‐218: Validation of An In‐Vivo Proton Range Verification Method for Reducing the Risk of Permanent Alopecia in the Treatment of Pediatric Medulloblastoma

Purpose:The clinical commissioning of a workflow for pre‐treatment range verification/adjustment for the head treatment of pediatric medulloblastoma patients, including dose monitoring during treatment.Methods:An array of Si‐diodes (DIODES Incorporated) is placed on the patient skin on the opposite side to the beam entrance. A “scout” SOBP beam, with a longer beam range to cover the diodes in its plateau, is delivered; the measured signal is analyzed and the extracted water equivalent path lengths (WEPL) are compared to the expected values, revealing if a range correction is needed. Diodes stay in place during treatment to measure dose. The workflow was tested in solid water and head phantoms and validated against independent WEPL measurements. Both measured WEPL and skin doses were compared to computed values from the TPS (XiO); a Markus chamber was used for reference dose measurements.Results:The WEPL accuracy of the method was verified by comparing it with the dose extinction method. It resulted, for both solid water and head phantom, in the sub‐millimeter range, with a deviation less than 1% to the value extracted from the TPS. The accuracy of dose measurements in the fall‐off part of the dose profile was validated against the Markus chamber. The entire range verification workflow was successfully tested for the mock‐treatment of head phantom with the standard delivery of 90 cGy per field per fraction. The WEPL measurement revealed no need for range correction. The dose measurements agreed to better than 4% with the prescription dose. The robustness of the method and workflow, including detector array, hardware set and software functions, was successfully stress‐tested with multiple repetitions.Conclusion:The performance of the in‐vivo range verification system and related workflow meet the clinical requirements in terms of the needed WEPL accuracy for pretreatment range verification with acceptable dose to the patient.

Developing Smart Cities Using Internet of Things: An Empirical Study

IoT is an emerging technology that creates a massive network of things communicating with one another. It encompasses a broad set of technologies, hardware and software stacks. Data, humans, devices and communication are critical elements of an IoT ecosystem. For a developing country such as India, which has quite limited technology penetration at the national level, an efficient architecture for IoT needs to be based on present technology advances, capabilities that provide affordable and sustainable solution, and entrepreneurial and social value. Smart city is an important concept for the development of any nation. It is crucial for government of India to offer different services to its citizens and IoT helps significantly to achieve this purpose. It will be possible to communicate transparently and seamlessly with large number of homogeneous and heterogeneous systems, while having selected access to data for designing numerous digital services. The primary purpose of this research paper is to study the role of IoT in development of Indian smart cities, understand the India IoT policy, find out the key drivers and advantages of IoT based smart city and identify the consumer preferences and demographics of Indian citizens who prefer IoT based smart city solutions.

Google Glass-Directed Monitoring and Control of Microfluidic Biosensors and Actuators.

Google Glass is a recently designed wearable device capable of displaying information in a smartphone-like hands-free format by wireless communication. The Glass also provides convenient control over remote devices, primarily enabled by voice recognition commands. These unique features of the Google Glass make it useful for medical and biomedical applications where hands-free experiences are strongly preferred. Here, we report for the first time, an integral set of hardware, firmware, software, and Glassware that enabled wireless transmission of sensor data onto the Google Glass for on-demand data visualization and real-time analysis. Additionally, the platform allowed the user to control outputs entered through the Glass, therefore achieving bi-directional Glass-device interfacing. Using this versatile platform, we demonstrated its capability in monitoring physical and physiological parameters such as temperature, pH, and morphology of liver- and heart-on-chips. Furthermore, we showed the capability to remotely introduce pharmaceutical compounds into a microfluidic human primary liver bioreactor at desired time points while monitoring their effects through the Glass. We believe that such an innovative platform, along with its concept, has set up a premise in wearable monitoring and controlling technology for a wide variety of applications in biomedicine.

Bandwidth-Efficient Modulation for Hybrid 10G/100G Optical Communication Networks

This letter proposes and experimentally demonstrates a novel scheme to generate 10G/100G hybrid signal in a short-reach optical communication system. The optical transmitter, which serves 10 and 100-Gb/s channels simultaneously, is realized using Nyquist frequency-multiplexing independent-sideband (NFM-ISB) modulation. For each optical wavelength, there are as many as four 10-Gb/s and one 100-Gb/s NFM-ISB digital channels carried by subcarrier multiplexing scheme, which can be cost-efficiently generated using only one set of optical transmitter hardware. More importantly, compared with the conventional system with independent optical transmitter, the proposed system requires at least five times less downlink optical transmitters, which can be translated into savings in cost, power consumption, and footprint.

Cascaded Multilevel Inverters for Reduce Harmonic Distortions in Solar PV Applications

The paper presents, a reverse system for sustainable energy function developed using the Cascaded H-bridge Multilevel Inverter (CHMI) that is able to produce a desired voltage by changing levels of DC voltages. A CHMI using Photovoltaic (PV) as source cells model was developed by means of the MATLAB Simulink. It was used to explore and validate the quality of the AC output voltage, harmonic traces of the output voltage and effects of varying switching schemes. The paper examine Sinusoidal Pulse Width Modulation (SPWM) technique applied to the CHMI in order to make sure a proficient voltage utilization and good harmonic band. The system simulation results using simulink program are shown and discussed together with a distinguish study for the various control techniques of the CHMI. A FPGA based controller is utilized to produce the PWM pulses for triggering the switches. By using this control method THD value less than 5% in hardware set up was obtained.

Information infrastructure development in NRU «MPEI»

The article describes the work on support and development of information infrastructure NRU «MPEI». Information infrastructure have different approaches to the defi nition. The authors defi ne the information infrastructure as a set of basic information services, computing, storage and data transmission systems that provide user access to information resources. New conditions dictate new approaches to building the education system in general and the educational process in each educational institution. NRU «MPEI» working to create a modern information infrastructure, including automated control systems, information resources and services, modular systems disciplines. This article describes the requirements for a modern information infrastructure of the NRU «MPEI», that provides students and teachers with the necessary services. Information infrastructure includes a set of software and hardware to ensure interaction between the participants of the educational process. All services and NRU «MPEI» system included in the unifi ed information educational environment (UIEE). Architecture UIEE NRU «MPEI» is displayed in the article. UIEE NRU «MPEI» is deployed on the basis of information network NRU «MPEI» and enables a comprehensive optimization of university management in various areas. Information and Computing Center supporting information and computer network NRU «MPEI», bought more than 4800 licenses in 43 different license versions of the software manufacturers. The server segment information network NRU «MPEI» contains a complex infrastructure and application servers for processing and storing information. The segment there are 20 high-performance server and storage system capacity of over 30 TB. In the server segment deployed complex systems to meet the needs in the various fi elds of activity NRU «MPEI», and the educational system to support the economic , scientifi c and human complex. Currently, ICC also pays great attention to the development of educational and innovation center, the initiative is aimed at improving the qualifi cations of teaching staff and training of students. For example, SAP technology are in fact the standard of corporate information systems for large enterprises, it is about 49.9% of the worldmarket. Therefore, every year, since 2008, the SAP Training Center - MPEI produces 40-45 graduates to work in energy companies and other industries. The preparation of an engineer is a challenge and a decision it is not possible without the widespread introduction of information and communication technologies in all spheres of activity of the university: teaching, research , management of the various spheres of activity . According to the authors , the use of modern information infrastructure for Engineering Education will allow to solve this problem effectively.

Design of an Embedded Sensor Network for Application in Energy Monitoring of Commercial and Industrial Facilities

The deployment of energy monitoring systems is well established for industrial facilities and commercial buildings, however these systems are insufficient where large variations in activity level (production variation, one-off events) are common. In such cases, accurate analysis of energy usage requires the deployment of a flexible embedded sensor network that can capture data at the required level of accuracy and granularity and can associate the energy usage data with the context and activity that has caused it. This research proposes an approach and a set of hardware and software tools for the monitoring of energy usage in technical building services and the association of that data with real-time production information in advanced manufacturing facilities.The system developed incorporates an embedded controller with sensors to monitor the physical environment, an integrated energy analyser to monitor electricity consumption and a visualisation interface that associate events in the physical world with the actual energy consumption recorded. The creation of a detailed time-stamped energy profile for the process can then be used in the identification of energy saving opportunities. A case study from a pharmaceutical facility was used to validate the operation of the system.

Density-based parallel skin lesion border detection with webCL

BackgroundDermoscopy is a highly effective and noninvasive imaging technique used in diagnosis of melanoma and other pigmented skin lesions. Many aspects of the lesion under consideration are defined in relation to the lesion border. This makes border detection one of the most important steps in dermoscopic image analysis. In current practice, dermatologists often delineate borders through a hand drawn representation based upon visual inspection. Due to the subjective nature of this technique, intra- and inter-observer variations are common. Because of this, the automated assessment of lesion borders in dermoscopic images has become an important area of study.MethodsFast density based skin lesion border detection method has been implemented in parallel with a new parallel technology called WebCL. WebCL utilizes client side computing capabilities to use available hardware resources such as multi cores and GPUs. Developed WebCL-parallel density based skin lesion border detection method runs efficiently from internet browsers.ResultsPrevious research indicates that one of the highest accuracy rates can be achieved using density based clustering techniques for skin lesion border detection. While these algorithms do have unfavorable time complexities, this effect could be mitigated when implemented in parallel. In this study, density based clustering technique for skin lesion border detection is parallelized and redesigned to run very efficiently on the heterogeneous platforms (e.g. tablets, SmartPhones, multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units) by transforming the technique into a series of independent concurrent operations. Heterogeneous computing is adopted to support accessibility, portability and multi-device use in the clinical settings. For this, we used WebCL, an emerging technology that enables a HTML5 Web browser to execute code in parallel for heterogeneous platforms. We depicted WebCL and our parallel algorithm design. In addition, we tested parallel code on 100 dermoscopy images and showed the execution speedups with respect to the serial version. Results indicate that parallel (WebCL) version and serial version of density based lesion border detection methods generate the same accuracy rates for 100 dermoscopy images, in which mean of border error is 6.94%, mean of recall is 76.66%, and mean of precision is 99.29% respectively. Moreover, WebCL version's speedup factor for 100 dermoscopy images' lesion border detection averages around ~491.2.ConclusionsWhen large amount of high resolution dermoscopy images considered in a usual clinical setting along with the critical importance of early detection and diagnosis of melanoma before metastasis, the importance of fast processing dermoscopy images become obvious. In this paper, we introduce WebCL and the use of it for biomedical image processing applications. WebCL is a javascript binding of OpenCL, which takes advantage of GPU computing from a web browser. Therefore, WebCL parallel version of density based skin lesion border detection introduced in this study can supplement expert dermatologist, and aid them in early diagnosis of skin lesions. While WebCL is currently an emerging technology, a full adoption of WebCL into the HTML5 standard would allow for this implementation to run on a very large set of hardware and software systems. WebCL takes full advantage of parallel computational resources including multi-cores and GPUs on a local machine, and allows for compiled code to run directly from the Web Browser.

Identifying the Performance of Resource Allocation Policies of Cloud Environment

The cloud computing is a set of hardware, networks, storage, service and interfaces that combine to deliver aspects of computing as a service. The cloud simply represents the internet. Continuous changes occur autonomously and unpredictably and are out of control of cloud provider. Hence to adopt these technologies in cloud platform advanced solutions have to be developed and to provide continuous services and However only the performance and energy trade offs are considered as weakest link in early cloud providers. The aim of this paper is to provide resource allocation policies for cloud environments to identify performance and energy trade-offs to the end user.

A comprehensive data acquisition and management system for an ecosystem-scale peatland warming and elevated CO<sub>2</sub> experiment

Abstract. Ecosystem-scale manipulation experiments represent large science investments that require well-designed data acquisition and management systems to provide reliable, accurate information to project participants and third party users. The SPRUCE project (Spruce and Peatland Responses Under Climatic and Environmental Change, http://mnspruce.ornl.gov) is such an experiment funded by the Department of Energy's (DOE), Office of Science, Terrestrial Ecosystem Science (TES) Program. The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. SPRUCE provides a platform for testing mechanisms controlling the vulnerability of organisms, biogeochemical processes, and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, and the cycling and release of CO2 and CH4 to the atmosphere). The SPRUCE experiment will generate a wide range of continuous and discrete measurements. To successfully manage SPRUCE data collection, achieve SPRUCE science objectives, and support broader climate change research, the research staff has designed a flexible data system using proven network technologies and software components. The primary SPRUCE data system components are the following: 1. data acquisition and control system – set of hardware and software to retrieve biological and engineering data from sensors, collect sensor status information, and distribute feedback to control components; 2. data collection system – set of hardware and software to deliver data to a central depository for storage and further processing; 3. data management plan – set of plans, policies, and practices to control consistency, protect data integrity, and deliver data. This publication presents our approach to meeting the challenges of designing and constructing an efficient data system for managing high volume sources of in situ observations in a remote, harsh environmental location. The approach covers data flow starting from the sensors and ending at the archival/distribution points, discusses types of hardware and software used, examines design considerations that were used to choose them, and describes the data management practices chosen to control and enhance the value of the data.

Type, Talk, or Swype: Characterizing and comparing energy consumption of mobile input modalities

It is reported that mobile users spend most of their time on texting SMS, Social Networking, Emailing, or sending instant messaging (IM), all of which involve text input. There are three primary text input modalities, soft keyboard (SK), speech to text (STT) and Swype. Each one of them engages a different set of hardware and consequently consumes different amounts of battery energy. Using high-precision power measurement hardware and systematically taking into account the user context, we characterize and compare the energy consumption of these three input modalities. We find that the length of interaction, or the message length, determines the most energy efficient modality. For short interactions, less than 14–30 characters, SK is the most energy efficient. For longer interactions, however, STT significantly outperforms both SK and Swype. When message length distributions of popular text activities are considered, STT provides near optimal energy consumption without requiring the user to predict the message length and decide between SK and STT. In terms of battery life, the choice of input modality makes significant differences. If users always choose SK for all their text activities, they will consume nearly 50% of the phone battery each day. Choosing STT over SK can save 30%–40% of the battery depending on the choice of STT software.

Studying Attacks to Information Systems Using Functional Networks

Information systems, i.e., the set of hardware and software tools that organizations use to collect and process data, are critical elements in any developed economy. Due to the intrinsic value of the information stored, government agencies and corporations alike are constantly on alert to heighten their infrastructure and data security due to threats from hackers and cyberterrorists. Information security (InfoSec) then aims at keeping information confidential, available, and at assuring its integrity, usually by detecting and preventing intrusions by external entities. However, protecting large-scale information systems is an increasingly difficult challenge; not only do attackers tend to be technically more sophisticated but they also show a higher degree of collaboration amongst themselves. Both factors concur in producing attacks, which are often of a previously unknown nature. Ensuring resilience against unpredictable, potentially high impact events forces organizations into allocating huge amounts of resources. Here, we propose that, in analogy with studies of functionally non-local complex systems, representing information systems as functional networksmay help detecting and classifying patterns associated with different families of attacks, and constructing proactive defense systems capable of detecting intrusion of previously unknown characteristics. As a prototypical example, we compare InfoSec with the study of functional brain networks, a field that has received increasing attention in the last decade, and that presents similar challenges (i.e., the identification of “normal” and “pathological” conditions).

AN ENHANCED RAILWAYS CONTROL OFFICE APPLICATION IMPLEMENTATION IN CLOUD ENVIRONMENT

As a result of continuous advancement of research and technology, travelling from one to place to another has become affordable and more at ease. There are opportunities which exist even for travel from Earth to Mars and other planets. The developments in the field of transportation have made a colossal impact in travelling for the passengers and other customers who rely on mass transportation of their goods. Many of the travel surveys reveal vital information about trips performed by people like origin, destination, mode, duration, distance and purpose of trips, as well as socio-economic and demographic data for investigation. This has made it possible to provide the best possible mixture of Fixed facilities, Flow entities, Operational plans, Storage facilities and Control systems wherein it allows the people and goods to trounce the abrasion offered by geographical spaces in a competent, secured and more affordable manner to attain the time and place benefit for the desired activity. The role of Indian Railways in maintaining train operations is effectively done by the Control Rooms in each of the seventy seven divisional/ area control offices. These Control Rooms are the nerve centre of the divisional operations. The effectiveness in maintaining the train schedules lies with the staff who are in charge of the Control Room operations. The Control Office never shuts down its operations and works 24X 7 to monitor and maintain fluidity of operations over its jurisdiction. In the recent days, train movements are supervised and captured in real time with the use of Control Office Application (COA) for effective monitoring of both scheduled and unscheduled trains. With the deployment of COA, a scheduled train can be started from one terminal to another by plotting the graph through getting information about the train from the stations manually, i.e., the information will be collected by a Controller on duty and the details collected include station name, train number, arrival time and departure time. This captured date is used for plotting the graph showing the movement of the train in the direction of its run and it also aids in fixing crossing or precedence of two or more trains at the best location based on conflict protocols. In this paper, we propose a new algorithm for voice-to-text conversion in mechanizing the scheme of information capture in the COA wherein the system would still capture the information from the station even when the Controller (human agent) is not available or when the inputs are received from more than one station. The proposed structure gives an opportunity to help us to overcome the human dependence and related errors in collection of information from the field. In the automation mode, when the human agent is physically not available, he will have the facility to switch on to the automated mode through which the information from the station can be collected as voice input, recorded and then converted into the text using the proposed algorithm. This would enable the application to use the data in an uninterrupted fashion for plotting the further movement of the train and also use the data for advance plotting in a more realistic fashion. The cloud is a set of hardware, networks, storage, services, and interfaces that facilitate the deliverance of computing as a service. In this type of cloud we are implementing our COA application software. It reduces the cost of hardware, hardware problems, servers.

MAG: A performance evaluation framework for database systems

A database system includes a set of different hardware and software resources with a large number of configuration parameters that affect and control the performance of database systems. Tuning these parameters within their diverse and complex environments requires a lot of expertise and it is a time-consuming, and often a misdirected process. Furthermore, tuning attempts often lack a methodology that has a holistic view of the database system. Therefore, in this paper, we introduce MAG, a layer-by-layer tuning framework that can be used to monitor, analyze, predict, and control database configuration parameters. In particular, the framework comprises three main components: NNMonitor predicts the system performance based on its given parameters; Analyzer identifies and determines the source of the problem and then directs to deal with the problem; and NNGenerator generates the experimental training sets exploited in training NNMonitor. The proposed approach focuses on the root causes of database performance problems. The approach further strives avoiding the repetitive trial-and-error process that is a characteristic of a lot of performance-tuning efforts. We experimentally demonstrate the effectiveness of the proposed framework through an extensive set of evaluations.

Very-High-Throughput Coherent Ultradense WDM-PON Based on Nyquist-ISB Modulation

We propose and experimentally demonstrate a very-high-throughput coherent ultradense wavelength division multiplexing passive optical network (UDWDM-PON) with its bandwidth efficiency enhanced using Nyquist-independent-sideband (N-ISB) modulation. The proposed optical line terminal (OLT) suggests 75 downlink optical subcarriers. For each optical subcarrier, there are as many as 16, 10-Gb/s N-ISB digital channels modulated on it, which can be efficiently generated using only one set of optical transmitter hardware. Experimental results show that the proposed UDWDM-PON is capable of accommodating 1200 10G users within an optical distribution network loss budget of 35.5 dB, and achieve a total throughput of 12 Tb/s and a spectral efficiency of 5.628-b/s/Hz. More importantly, the proposed system with spectral- and bandwidth-efficient N-ISB requires 16 times less downlink optical transmitters at the OLT, which can be translated into savings in cost, power consumption, and footprint. In addition, key techniques, such as N-ISB modulation in a PON system, frequency-locked optical multicarrier generation, and digital pre-equalization, are also studied.

Complexity of a car sorting algorithm

In this article a problem of sorting cars in a freight train is considered and its mathematical formulation is given. The sorting is executed on a so called sorting yard hump. The yard hump consists of a small hump with a tree of railroads starting on the top of the hump and branching out to k rail ends with controls that allow to direct a car moving from the top to a given end. On each run, the train is distributed to the end paths and after that collected back from fragments on the paths. The maximum number of runs of the whole train to sort it and overall complexity of the algorithm are found. Some features of this method are similar to the main idea of the well know procedure of sorting perfocards in the classical Hollerith set of hardware. The initial data is a permutation of the set 1: n, where each car is associated with its position in the desired train sequence. In solution we use a partition of the permutation of 1: n to monotone segments. For example, the permutation 3, 8, 2, 6, 1, 4, 5, 7 with n = 8 is divided to segments (3, 2, 1), (4), (6, 5), (8, 7). These segments are easier defined in terms of the permutation inverse to the given one. It is treated as a string consisting of numbers, and each part of the partition corresponds to a maximal monotonically decreasing set of numbers in the list of elements. In our example the inverse permutation 5, 3, 1; 6; 7, 4; 8, 2 is divided to 4 substrings by separators “;”. Let p be the number of parts in this partition, and k is the number of roads in the hump. Then the number of runs of the train through the hump to get n, n–1, …, 2, 1 does not exceed ┌logk p┐ ≤ ┌logk n┐, and this estimation is reached by the proposed algorithm.