Abstract:
A method and an apparatus for efficient resource sharing are presented. The apparatus includes a central unit having a plurality of surfaces on the outside, the central unit holding a resource. Compartments are coupled to the central unit, each of the compartments being placed adjacent to one of the surfaces of the central unit. Each compartment has a platform to support an object, and has a sensor that reads an output signal indicating that the object in the compartment has finished accessing the resource from the central unit. A computation unit receives and processes the output signal from each of the compartments. The sensor in the apparatus may be located in the central unit instead of in the compartments.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This patent application is a Continuation-in-Part of U.S. patent application Ser. No. 11/223,494 filed on Sep. 9, 2005, which claims the benefit of U.S. Provisional Patent Application No. 60/608,689 filed on Sep. 10, 2004 and U.S. Provisional Patent Application No. 60/680,313 filed on May 13, 2005. Contents of the provisional applications are incorporated by reference herein. 
    
    
     FIELD OF INVENTION 
     This invention relates generally to a system for detecting the presence of a threatening item, and more particularly to a system for detecting the presence of a threatening item using a plurality of tests in parallel. 
     BACKGROUND 
     Today, checkpoint security systems in public places like airports or government buildings typically include some combination of an imaging test, a metal detector, and a chemical test. The chemical test usually uses the table-top explosive trace detection (ETD) machine in which a swab or an air sample is taken from an object (e.g., a bag) and tested for trace explosive materials. 
     Unfortunately, the security check systems that are currently in use are not as reliable as they could be. For example, the X-ray tests identify threatening items based on object densities, and many innocuous objects have densities that are similar to those of some threatening items. Naturally, the rate of false-negative is high. With the imaging test involving X-ray or CT-scan, the accuracy of the test depends largely on the alertness and judgment of a human operator who reviews the images as the bags are scanned. While several systems include automatic visual classification of suspect items, reliance on human alertness and judgment still plays a major role in these systems. Due to distractions, fatigue, and natural limitation on human attention span, a check system that relies so heavily on human judgment cannot reach an optimal level of accuracy. Moreover, because imaging test relies heavily on the visualization of objects being tested, a passenger can disguise or hide a harmful threatening item and avoid detection by the imaging test. 
     Attempts have been made to increase the accuracy of a checkpoint security system by using a combination of tests, such as imaging, metal detector, and a chemical test. Typically, the tests are performed by utilizing three separate equipments and placing them next to one another. Objects are tested by the separate equipments separately and sequentially, one test after another. For example, an airport security system may employ an X-ray image test and subject only bags that are indicated as being suspect by the X-ray image test to a chemical test. Similarly, as for passengers, they may first be asked to pass through a preliminary metal detection portal, and be subjected to a more stringent metal detector test performed by a human operator only if an alarm is raised by the preliminary portal test. 
     A problem with this type of serial/sequential combination of tests is that the overall accuracy depends heavily on the accuracy of each individual test, and in some cases on the accuracy of the first test. For example, if the chemical test is not used unless a bag fails the X-ray imaging test, the use of the chemical test is only helpful if the X-ray imaging test accurately identifies the suspect bags. If the operator reviewing the X-ray images misses a potential threatening item, the fact that the chemical test is readily available does not change the fact that the potential threatening item passed through the security system. 
     While using multiple tests on every passenger and luggage would be an obvious way to enhance the accuracy of security checks, such solution is not practical because it would result in passengers spending an inordinate amount of time going through the security checks. Moreover, such system would be prohibitively costly. For a practical implementation, the accuracy of the security check tests is balanced by—and compromised by—the need to move the passengers through the system at a reasonable rate. Also, if a test that yields a high rate of false-positives like the X-ray test is used as the first test, the flow of passengers is unnecessarily slowed down because many bags that do not contain a threatening item would have to be subjected to the second test. 
     A system and method for moving the passengers through a security checkpoint at a reasonable rate without compromising the accuracy of the security check tests is desired. 
     SUMMARY 
     In one aspect, the invention is an apparatus for sharing a resource. The apparatus includes a central unit having a plurality of surfaces on the outside, the central unit holding a resource. Compartments are coupled to the central unit, each of the compartments being placed adjacent to one of the surfaces of the central unit. Each compartment has a platform to support an object, and has a sensor that reads an output signal indicating that the object in the compartment has finished accessing the resource from the central unit. A computation unit receives and processes the output signal from each of the compartments. 
     The sensor in the apparatus may be located in the central unit instead of in the compartments. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram illustrating the main components of a multi-threat detection system in accordance with the invention. 
         FIG. 2  is a block diagram of an exemplary embodiment of the multi-threat detection system. 
         FIG. 3  is a block diagram illustrating the modules of the computation unit for executing a threatening item identification method. 
         FIG. 4  is an exemplary embodiment of the multi-threat detection system including a single test unit and multiple object units, wherein the test unit has flat outer surfaces. 
         FIG. 5  is a block diagram showing the test unit and the object units. 
         FIG. 6  is another exemplary embodiment of the multi-threat detection system wherein the object is a human being (or any of other animals). 
         FIG. 7  is yet another exemplary embodiment of the multi-threat detection system for testing inanimate objects and human beings. 
         FIG. 8  is a perspective view of an exemplary embodiment of the multi-threat detection system including a single test unit and multiple object units. 
         FIG. 9  is a cross-sectional view of an alternative embodiment of the multi-threat detection system wherein the central unit has a curved outer surface. 
     
    
    
     DETAILED DESCRIPTION OF THE EMBODIMENTS 
     Embodiments of the invention are described herein in the context of a checkpoint security system. However, it is to be understood that the embodiments provided herein are just exemplary embodiments, and the scope of the invention is not limited to the applications or the embodiments disclosed herein. For example, the system of the invention may be useful for automated testing of small parcels and mail, non-security-related testing, and nondestructive testing for any purpose including checking packaged consumable items (e.g., food, drugs), among others. 
     The multi-threat detection system of the invention is useful for detecting the presence of various threatening items. A “threatening item” is any substance and or a combination of substances and objects that may be of interest to a security system including but not limited to explosives, explosive devices, improvised explosive devices, chemical warfare agents, industrial and other chemicals that are deemed hazardous, biological agents, contraband, drugs, weapons, and radioactive materials. The invention provides an automated system for performing different types of tests to screen multiple threatening items fast, such that multiple objects can be examined in a relatively short period of time. Furthermore, the system of the invention decreases the reliance on human operators, using instead a computation unit that determines a risk factor based on concurrent acquisition and processing of the different test results. Thus, the system provides the much-needed method of increasing the accuracy of a security check test without compromising the throughput. 
     An “ionized radiation test,” as used herein, is intended to include any form of test that emits ionized radiation such as nuclear, X-ray, or Gamma ray radiation. Examples of X ray methods include standard X-ray transmission, backscatter methods, dual or multi energy methods as well as CT-scan. Examples of nuclear radiation source testing include methods such as Thermal Neutron Analysis, Pulsed fast neutron analysis, backscatter, and terahertz test, among others. A “non-ionizing test” includes methods that use a non-ionizing electromagnetic (EM) radiation source, such as those that expose the material to a pulsed EM field and acquire the return pulse. These methods include use of high-millimeter waves, Nuclear Magnetic Resonance (NMR) spectroscopy, Electron Spin Resonance (ESR) and Nuclear Quadrapole Resonance (NQR), among others. An additional potential non-ionizing source includes Tetrahertz. In addition, “non-ionizing tests” also include methods used in detection of conductive materials that subject an object to electromagnetic fields, either constant or pulsed wave, and detect the corresponding direction of changes in the field. “Chemical analysis” is intended to include methods of substance detection including ion mobility spectrometry (IMS), ion trap mobility spectroscopy (ITMS), capture detection, chemiluminescence, gas chromatography/surface acoustic wave, thermo-redox, spectroscopic methods, selective polymer sensors, and MEM based sensors, among others. 
     A “biological classification” classifies biological threats (e.g., organisms, molecules) according to guidelines indicating the potential hazard level associated with toxins, bioregulators, and epidemically dangerous organisms (such as viruses, bacteria, and fungi). A “biometric classification test” includes standard discrete biometric methods such as finger prints, as well as physio-behavioral parameters indicative of suspect behavior. 
     As used herein, “simultaneously” is intended to mean a partial or a complete temporal overlap between two or more events of the same or different durations. For example, if Event A begins at time 0 and ends at time 10 and Event B begins at time 2 and ends at time 10, Event A and Event B are occurring simultaneously. Likewise, Event C and Event D that both start at time 0 and end at time 7 are also occurring simultaneously. “Sequentially,” on the other hand, indicates that there is no temporal overlap between two or more events. If Event E begins at time 0 and ends at time 6 and Event F begins at time 7 and ends at time 10, Events E and F are occurring sequentially. 
     A “parameter,” as used herein, is intended to include data and sets of data and functions, either static or dynamic. 
     A “threat determination function,” as used herein, is intended to include a function or sets of functions that define a condition that indicates the presence of a threat. Theses function(s) can be a static value, sets of static values, or a dynamic calculation. The function(s) can be either rule-based or based on other methods such as neural network. 
     A “risk factor” indicates the likelihood that the threatening item is present in the object. A “set” of risk factors may include one or more risk factors. 
       FIG. 1  is a block diagram illustrating the main components of a multi-threat detection system  10  in accordance with the invention. As shown, the multi-threat detection system  10  includes a test unit  20 , a computation unit  40 , and an object unit  60  that are coupled to one another. The object unit  60  has a mechanism that is designed to hold an object (e.g., a bag or a piece of luggage) that is being examined. The test unit  20  includes various test sources and/or equipment such as a radiation source for an X-ray exam, a chemical analysis unit for a chemical exam, RF coils and or other magnetic field inductions for a non-ionizing exam. The computation unit  40 , which has a processor and a memory, is configured to receive inputs from the test unit  20  and the object unit  60  and process the inputs to generate a risk factor. The risk factor indicates the likelihood of the object in the object unit  60  containing a threatening item. Optionally, there may be a communication unit that may include a user interface unit (not shown) that is coupled to the computation unit  40  so that the risk factor and a corresponding alert can be communicated to an operator of the multi-threat detection system. 
     The tests that are incorporated into the test unit  20  may be any currently known tests for screening threatening items, and is not limited to the examples mentioned herein. There may also be a plurality of object units coupled to the test unit  20  and the computation unit  40  so that multiple objects can be examined almost at the same time. 
       FIG. 2  is a block diagram of an exemplary embodiment of the multi-threat detection system  10 . 
     The object unit  60  has one or more doors  61  through which an object  62  can be placed in the object unit  60  to be subjected to various tests. In some embodiments, the object  62  remains stationary on a platform in the object unit  60 . In other embodiments, the object  62  is moved across the object unit  60  through a moving mechanism  67 . The moving mechanism  67  may be coupled to a grasping and/or rotating mechanism  64 , which may be a robotic mechanism that is capable of holding the object  62  and positioning and rotating the object  62  in a desired location at the desired test angle. In the embodiment shown, the moving mechanism  67  is a type of pulley system, an x-y positioner system  65 , a linear motor, or any combination of these systems, and is coupled to the grasping and/or rotating mechanism  64 . In an alternative embodiment, the moving mechanism may be a conveyor belt that carries the object  62  through different test stages. 
     The object unit  60  includes an automated receiver  69  that automatically provides extra information about the owner of the object  62 . In some embodiments, the extra information may include ticketing information. In other embodiments, additional information about the owner, such as his name, citizenship, travel destination, etc. may also be made available by the automated receiver  69 . The automated receiver  69  may be implemented with digital/magnetic tagging, RF tagging, or other smart card scan that identifies the owner/carrier of the object  62 . This automatic correlation between the object  62  and its owner/carrier facilitates identifying the responsible person if a threatening item is found. The object unit  60  has one or more doors  61  through which the object can be removed. In some embodiments, the doors  61  are locked automatically upon the identification of a threatening item as part of the operational security protocols. 
     In this exemplary embodiment, the ionized radiation test unit  20  has an X-ray source subunit  22 , a chemical analysis subunit  30 , and non-ionizing source subunit  36 . The X-ray examination is done by an X-ray source  24  generating a beam and directing it toward the object  62 . The X-ray source  24  is preferably supported by a rotating mechanism  26  that allows the beam to be pointed in different directions, as it may be desirable to adjust the direction of the beam according to the size and the position of the object  62 . A plurality of sensors  66  are located in the object unit  60  and positioned to receive the X-ray beams after they pass through the object  62 . Additional sensors  66  can be positioned to acquire back scatter radiation as well. The beam is received by the sensors  66  after passing through the object  62 . The sensors  66  generate output signals based on the received beam and feed the output signals to the computation unit  40 . Where X-ray is used as one of the tests, the walls of the X-ray subunit  22  and the object unit  60  are shielded to contain the radiation within the object unit  60 . 
     The chemical analysis may be performed by taking a sample from the object  62  and running the sample through the chemical analysis subunit  30 . A path implemented by a flow device such as a rotational flow device  32  connects the grasping and/or rotating mechanism  64  to the chemical analysis subunit  30  so that the sample from the object  62  can be transported to the chemical analysis subunit  30 . The chemical analysis may be based on, for example, ion mobility spectroscopy, or newer methods such as selective polymers or MEMs-based sensors. Where ion mobility spectroscopy is used, the chemical analysis subunit  30  includes an ionization reaction chamber  28 . An air flow is generated by a vacuum pump  33  for obtaining a gas sample from the object unit  60 . The gas sample travels through the adjustable closure pipes  32 , which have particle acquisition pores  63  in proximity to the object  60  for obtaining gas samples. The rotational flow device  32  and the particle acquisition pores  63  provide a means for continuous-contact gas agitation and particle acquisition for continual analysis while the object moves inside the object unit  60  for other tests. The particle acquisition pores  63  may be placed on the grasping and/or rotating mechanism  64  that moves the object  62  across the object unit  60 , such as the robotic arm or the conveyor belt mentioned above. The gas sample enters the chemical analysis subunit  30 . In an exemplary embodiment using the IMS method, the gas sample enters an ionization reaction chamber  28  through the rotational flow device  32  and becomes ionized by an ionization source. The ionized gas molecules are led to a collector plate (not shown) located in the ionization reaction chamber  28  by an electric field within the chamber  28 . The quantity of ions arriving at the collector plate as a function of time is measured and sent to the computation unit  40  in the form of one or more output signals. A microprocessor at the chemical analysis subunit  30  may convert the quantity of ions to a current before sending the current to the computation unit  40 . IMS is a well-established method. 
     Optionally, the chemical analysis subunit  30  contains an interfacing module  35  to a biological detection system. If a biological detection system is incorporated into the test unit  20 , a biological classification of the object can be obtained. A biological detection system that detects molecular materials could utilize one of the chemical analysis methods. A system that is intended to identify an organism, such as Anthrax, would utilize an automated DNA testing based on automated polymerase chain reaction (PCR) according to the current state of technology. 
     The non-ionizing source subunit  36  may contain a radiofrequency (RF) source and/or a magnetic source, such as RF coils  38  and antennae for NQR testing and/or eddy current testing. These tests provide information on the chemical compositions of the object and or information on the existence of metallic and other conductive materials. Magnetic sources may be a plurality of sources that vary in size and strength, so that the location of a threatening item can be detected as well as its presence. Radiofrequency waves and/or a magnetic field is directed at the object  62  and the sensors  66  receive the wave and/or the field after it passes through the object  62 . For example, where the subunit  36  is a metal detector, the metal detector may transmit low-intensity magnetic fields that interrogate the object  62  as it passes through the magnetic fields. A transmitter generates the magnetic field that reacts with the metal objects in its field and the sensors  66  measure the response from this reaction. The sensors  66  send the measurement result to the computation unit  40 . 
     In addition to the X-ray exam, ion mobility spectrometry, and the non-ionizing source test used in the embodiment of  FIG. 2 , any other test may be employed by the multi-threat detection system  10  if considered useful for the particular application. Also, the X-ray exam, the ion mobility spectrometry, and the non-ionizing source test may be substituted by different tests as deemed fit by a person skilled in the art. Preferably, each of the subunits  22 ,  30 ,  36  is designed to be replaceable independent of other subunits. Thus, substituting one test with another will likely be a matter of replacing one subunit with another. 
     The sensors  66  may be a fused-array sensor capable of collecting multiple information either in parallel or in a multiplexed manner. Information collected may include any test results such as X-ray, terahertz ray, gamma ray, RF, chemical, nuclear radiation, and current information. 
     The computation unit  40  includes a processor  42 , a memory  44 , and a power supply  46 . Using a multi-variant method such as the method described below in reference to  FIG. 3 , the computation unit  40  determines the risk factor, which indicates the likelihood that an object will contain a threatening item. The computation unit  40  has a communication interface  50  through which it can send visual and/or audio alerts in any mode of communication, preferably wirelessly, if an object is likely to contain a threatening item. There is also at least one open interface  95  that allows the computation unit  40  to communicate with another apparatus, such as a platform for human portal system or a platform for biometric inputs. The open interface  95  may allow wired or wireless connections to these other apparatuses. 
     The chemical analysis test results may be sent directly from the collector plate in the chemical analysis subunit  30  to the computation unit  40 . If desired, however, the data from the collector plate may be sent to one or more sensors  66  in the object unit  60  and sent to the computation unit  40  indirectly from the sensors  66 . When using other methods such as passive sensors, particles can be routed directly to sensors  66 . Other data, such as X-ray data, are collected by the sensors  66  and sent to the computation unit  40 . As used herein, “sensors” include any type of device that is capable of making a physical or electrical measurement and generating an output signal for the computation unit  40 , such as sensors  66  in the object unit  20  and the collector plate in the chemical analysis subunit  30 . 
     Although  FIG. 2  shows the test unit  20 , the computation unit  40 , and the object unit  60  as three separate components, the division is conceptual and the physical units do not necessarily have to correlate with the conceptual division. For example, all three units may be contained in one housing, or the test unit  20  and the object unit  60  may be contained in the same housing while the computation unit  40  is in a remote location. 
       FIG. 3  is a block diagram illustrating the modules of the computation unit  40  for executing a threatening item identification method. As described above, the computation unit  40  receives inputs from the test unit  20  and/or the object unit  60 . These inputs originate as raw data collected by the sensors  66  and/or the collector plate in ion mobility spectrometry (or another chemical sensor). As shown in the diagram, the method of the invention uses a set of functional modules  116 ,  118 ,  120 ,  122 ,  124 ,  126 ,  128 ,  206 ,  208  to process the various inputs from the sensors  66  and the sensor in the test unit  20  (e.g., the collector plate). Using these modules, values are calculated for various parameters such as texture, density, electrical conductivity, molecular classification, location classification, radiation classification, visual classification, biological classification, and biometric classification for the object  62 . Where the object  62  is something like a bag that contains multiple components, the components may be automatically divided according to texture, density, conductivity, etc. so that each component is classified separately. 
     In the particular embodiment of the threatening item identification method that is shown in  FIG. 3 , the active radiation (e.g., X-ray) detection results are used for determination of texture classification, density classification, shape context classification, location classification, and visual classification. The radioactive level of the object may be determined for radiation classification. Current data or induced EM field responses are used for parameters such as texture classification, conductivity classification, and location classification. The magnetic response is used for calculating parameters such as molecular classification, density classification, and location classification. Any chemical analysis result is used for molecular classification. Output signals from the sensors  66  and output signals from the chemical analysis subunit  30  are fed to the different modules in parallel, so that the values for all the parameters of the classification areas such as texture, density, etc. can be determined substantially simultaneously. 
     After the parameters based on values and functions for each of these classification areas is determined, the values are collectively processed in a multi-variant data matrix module  300  to generate a risk factor. The multi-variant data matrix  300  arranges the plurality of classification parameters from function matrices  116 ,  118 ,  120 ,  122 ,  124 ,  126 ,  128 ,  206 ,  208 ,  210  into an n-dimensional data matrix. For instance, visual classification function matrix  124  would yield numerous visualization data [V] as a function of number of (1 . . . n) and measurement and angles ( 101  ) depending on the number of rotations performed by the grasping and/or rotating mechanism  64 , so one form of data would be V=f(Φ)n. Additionally, a series of visualization data [V] related to density parameters [D] at each angle Φ would yield the set of parameters V=f(D, Φ, n). Another set of parameters fed into the multi-variant data matrix  300  would be conductivity classifications from the conductivity classification functions matrix  120  and would similarly yield an array of interrelated parameters, for example conductivity [Z] as having varying intensities (i) as a function of location (l) yielding one set of Z=f(i,l). These three exemplary functions V=f(Φ, n), V=f(D, Φ, n), and Z=f(i,l) would be arranged in the multi variant data matrix  300  in such a way that provides multiple attributes for particular three-dimensional locations, as well as global attributes, throughout the screened object. More generally, all classification function matrix blocks will produce numerous parameter sets, so that an n-dimensional parameter matrix is produced for processing in block  310 . 
     The n-dimensional parameter matrix generated in block  310  enables numerous calculations and processing of dependent and interdependent parameters to be performed in block  310 . The parameters from the multi-variant data matrix module  300  is submitted to the threat determination functions, which include running sets of hybrid calculations. Hybrid calculations include combinations of rule-based and other methods (such as neural network or other artificial intelligence (AI)-based algorithms) and comparison of the result against real-world knowledge criteria and conditions (block  310 ). In some embodiments, an example of a rule-based decision would combine testing some or all of the parameter(s) against thresholds. For example, a condition such as “If texture classification T(Φ,L)n&gt;3, density classification D(Φ,L)n&gt;4, conductivity classification Z(i,l)n&gt;4, location classification&gt;3, and radiation classification&gt;1” could be used as a condition for determining one type of risk factor and possibly generating an alert. Calculations may be any simple or complex combination of the individual parameter values calculated by test block  310  to determine sets of risk factors. Sets of risk factors represent various categories of threats that are likely to be present in the object. For instance, there may be a category of threat functions associated with the likelihood of a biological event which would produce a risk factor for this category, there may also be a category of threat functions associated with the likelihood of an explosive threat which would produce a risk factor for the explosive category, and yet there may be a category threat functions associated with a general likelihood evoked by a combination of attributes not necessarily specifically to the material type. Different calculations may yield a number of risk factors within each category. The threat functions include test conditions and apply criteria based on pre-existing real world knowledge on signals and combinations of signals identifying threats. 
     If a high-enough risk factor is determined that the preset set of threat thresholds are satisfied, depending on the embodiment, the location, quantity, and type of the threatening item may be estimated (block  320 ), an alert may also be generated (block  330 ). Whether a risk factor is high enough to trigger the alert depends on the sensitivity settings within the system, which has a default setting and is reconfigurable by the user. An “alert” may include a visual or audio signal for notifying the operator that a threatening item may have been identified, and may also include taking other operational actions such as closure/locking of the door  61  in the object unit  60 . Optionally, a signal (e.g., a green light) may be generated to indicate that an object is clear of threatening items (block  325 ). 
       FIG. 4  is a cross-sectional view of an exemplary embodiment of the multi-threat detection system  10  including a single test unit  20  and multiple object units  60   a - 60   e .  FIG. 8  is a perspective view of the system  10 . In this embodiment, the centrally located test unit  20  has flat outer surfaces that interface the object units  60   a - 60   e . As shown, the test unit  20  is located centrally with respect to the object units  60  so that an object can be tested by the test unit  20  regardless of which object unit it is in. The test unit  20  and the object unit  60  may be made of any material with structural integrity including various metals (e.g., steel) or composite material. Preferably, there is a rotating mechanism in the test unit  20  that allows the direction of the test beam, etc. to be adjusted depending on which object is being tested. Once all the object units are filled, the test unit performs tests on the objects by turning incrementally between each object unit  60  as shown by the arrows. Some tests are performed sequentially. For example, if an X-ray test is performed, the X-ray beam is directed from the test unit  20  to the multiple object units  60   a - 60   e  sequentially, e.g. in a predetermined order. However, other tests are performed simultaneously for the multiple object units  60   a - 60   e . For example, if a chemical analysis test is performed, a sample of each object in the multiple object units  60   a - 60   e  can be taken simultaneously, as each object unit has its own rotation flow device  32 , grasping and/or rotating mechanism  64 , and particle acquisition pores  63 . Thus, depending on the tests that are included in the particular embodiment, the overall testing may be partly sequential and partly simultaneous for the multiple object units  60   a - 60   e . All the test data are sent to the computation unit  40 , preferably as soon as they are obtained. 
     The output signals from the sensors  66  (and the collector plate of the chemical analysis subunit  30 , if applicable) may be processed by a single computation unit  40  or a plurality of computation units  40 . Where a single computation unit  40  is used, the computation unit  40  keeps the objects separate so that it yields five different results, one for each object  62 . 
     The embodiment of  FIG. 4  allows multiple objects to be processed quickly compared to the current security check system where passengers form a single line and one object (e.g., bag) is processed at a time. Therefore, all the tests incorporated into the test unit  20  can be performed for each of the objects in the object units  60   a - 60   e  without compromising the traffic flow. 
     The multi-threat detection system  10  of  FIG. 4  may be designed as a modular unit, so that the number of object units  60  is adjustable. Thus, if a first area is getting heavy traffic while traffic in a second area has slowed down, a few of the object units from the second area can be used for the first area by simply being detached from one test unit  20  and being attached to another test unit  20 . The detaching-and-attaching mechanism may use hook systems and/or a clasping/grasping/latching mechanism. This flexibility results in additional cost savings for public entities that would use the multi-threat detection system  10 . The object units  60 a- 60 e are substantially identical to one other. 
     Additionally, the platform on which the object  62  is placed in the object unit  60  may have a sensor, such as a weight or optical sensor, that signals to the test unit  20  whether the particular object unit  60  is in use or not. So, if only object units  60   a ,  60   b ,  60   d , and  60   e  are used for some reason, the test unit  20  will not waste time sending test beams and collecting samples from the empty object unit  60   c  and the system  10  will automatically optimize its testing protocols. The system  10  may include a processor for making this type of determination. A sensor is placed either in each object unit  60  or in the test unit  20  to detect an output signal indicating that an object in the object unit  60  has been tested. 
     Although the particular embodiment shows the units as having hexagonal shapes for a honeycomb configuration, this is just an example and not a limitation of the invention. For example, the test unit  20  may have any polygonal or curved cross section other than a hexagon.  FIG. 9 , for example, shows a cross-sectional view of a multi-threat detection system  10  wherein the test unit  20  has a curved outer surface (as opposed to flat outer surfaces as in the embodiment of  FIG. 4 ). The shapes of the object units  60   a - 60   e  are adapted so they can efficiently and securely latch onto the test unit  20 . Furthermore, the structure allows a resource in a central unit (e.g., the test unit  20 ) to be shared among the surrounding compartments (e.g., object units  60 ) in a fast and space-efficient manner, making the structure useful for various applications other than detection of threatening objects. For example, where multiple objects need to be encoded with a piece of data, the data source can be placed in the central unit so that objects in the surrounding compartments can read the data. In a case of laser etching, objects in the compartments could receive data encoding from the central unit. 
       FIG. 5  is a block diagram showing the test unit  20  and the object units  60   a - 60   e . In the particular embodiment, a single computation unit  40  is used for all the object units  60   a   60   e.  Each of the object units  60   a - 60   e  contains a moving device, such as a mechanical mechanism, multi axis manipulator, robotic mechanism, a conveyor belt, or any other rotating and linear mechanism and a sensor array, as described above in reference to  FIG. 2 . The moving device allows both linear and rotational movement. The test unit  20  has four subunits: an ionized radiation source subunit, a chemical analysis subunit, a non-ionizing radiation source subunit, and a magnetic field induction subunit. Each of the object units  60   a - 60   e  is coupled to the test unit  20  and the computation unit  40 . 
       FIG. 6  is another exemplary embodiment of the multi-threat detection system  10  wherein the object is a human being (or any of other animals). In the particular embodiment that is shown, the test unit  20  has two object units  60   a ,  60   b  attached to it. Naturally, tests involving radiation will be used with caution, by choosing appropriate radiation sources and parameters when the “objects” being tested are human beings. If desired, a camera may be installed somewhere in the test unit  20  or the object unit  60   a  and/or  60   b  to obtain images of objects in order to obtain a biometric classification and/or transmit images to an operator. 
       FIG. 7  is yet another exemplary embodiment of the multi-threat detection system  10  for testing inanimate objects and human beings. The particular embodiment has the test unit  20  with five object units  60   a - 60   e  for testing inanimate objects and a portal  60   f  for human beings or animals to pass through. The test unit  20  tests objects in the object units  60   a - 60   e  and human beings in the object unit  60   f  that are in each of the object units  60   a - 60   f . However, all the object units and both test units would still feed signals to a single computation unit  40 . 
     The invention allows detection of threatening items with increased accuracy compared to the currently available system. While the currently available systems use a sequence of separate equipment, each equipment using only one test and generating a test result based only on that one test, the system of the invention relies on a combination of a plurality of parameters. Thus, while a bomb that has a low level of explosive and a small amount of conductive material may escape detection by the current system because both materials are present in amounts below the threshold levels, the object could be caught by the system of the invention because the presence of a certain combination of indicative materials and vicinity parameters included in the threat determination functions could trigger an alarm. The use of combinations of parameters allows greater flexibility and increased accuracy in detecting the presence of threatening items. 
     The invention also allows detection of a general threatening item, material deformation, and fractures in the case of a nondestructive testing. This is different from the current system that targets specific items/materials such as explosives, drugs, weapons, etc. By detecting the presence of a general combination of potentially hazardous materials, the system of the invention makes it more difficult for creative new dangerous devices to pass through the security system. 
     While the foregoing has been with reference to particular embodiments of the invention, it will be appreciated by those skilled in the art that changes in this embodiment may be made without departing from the principles and spirit of the invention.